视觉语义编码和自然电影的识别通过高密度扩散光学断层扫描
Wiete Fehner1,2, Morgan Fogarty2, Jerry Tang3
1Imaging Science, Washington University in St. Louis, St. Louis, MO, USA.
bioRxiv : the preprint server for biology
|December 22, 2025
概括
高密度扩散光学断层扫描 (HD-DOT) 在自然主义电影观看期间成功解码大脑活动. 这种先进的成像方法揭示了详细的语义表示,推进了神经科学和临床应用.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 生物医学工程 生物医学工程
背景情况:
- 了解大脑的语义表示对于神经科学和临床应用至关重要.
- 现有的大脑编码/解码模型使用受限制的环境或有限的常规功能近红外光谱 (fNIRS).
- 传统的fNIRS受到稀疏采样和块设计范式的限制.
研究的目的:
- 调查高密度扩散光学断层扫描 (HD-DOT) 对于使用自然电影刺激的语义编码和解码的有效性.
- 评估HD-DOT在捕捉大脑中的高维语义表示的能力.
- 弥合fMRI级语义映射和光学成像可访问性之间的差距.
主要方法:
- 从六名参与者收集了3.5小时的自然主义电影观看数据.
- 利用高密度扩散光学断层扫描 (HD-DOT) 进行先进的断层光学成像.
- 开发了编码模型来预测voxel级大脑反应,并进行了解码分析来识别观看的片段.
主要成果:
- 编码模型稳定地预测了声音级响应,生成了与fMRI研究相似的语义类别地图.
- 解码分析表明,HD-DOT响应包含足够的语义信息来识别观看的电影片段.
- 在参与者之间确定了一个共享的低维语义空间,并揭示了可解释的语义维度 (例如,社会代理人,物体,场景).
结论:
- HD-DOT可以有效地从自然主义电影刺激中恢复分布式,高维的语义表示.
- 这项研究验证了HD-DOT作为语义大脑映射的可行工具,它比传统方法具有优势.
- 这些发现为更容易获得和生态有效的语义处理的大脑成像研究铺平了道路.
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